Research on Recommender Systems (RSs) has evolved across disciplines, from a focus on technical optimization to a broader interest in these systems’ societal role and impact. In this paper, we distinguish between two broad research orientations—technical and social—and identify three research waves that reflect shifting assumptions and research questions of both orientations. We discuss how assumptions within each research orientation have influenced the other over time, shaped by RSs becoming more deeply embedded in real-world, multi-sided applications. This evolving interplay has led to growing convergence around the central question: why do recommenders recommend? Addressing this question requires perspectives that span both technical and social domains, underscoring the importance of interdisciplinary collaboration. By charting this research evolution, this paper aims to support interdisciplinary exchange and collaboration in the field. It encourages researchers to explicitly acknowledge and revisit the assumptions that drive their research, and identifies which research questions arise more naturally and which may require additional effort.